Using a Bayesian Network Induction Approach for Text Categorization
Proceedings of the Fifteenth International Joint Conference on Artificial Intelligence. Information Retrieval. Pages 745-749.
Abstract
We investigate Bayesian methods for automatic document categorization and develop a new approach to this problem. Our new approach is based on a Bayesian network induction which does not rely on some major assumptions found in a previous method using the Bayesian independence classifier approach. The design of the new approach as well as its justification are presented. Experiments were conducted using a large-scale document co ll ection from Reuters news articles. The results show that our approach outperformed the Bayesian independence classifier as measured by a metric that combines precision and recall measures.
@inproceedings{ijcai1997p108,
title = {Using a Bayesian Network Induction Approach for Text Categorization},
author = {Lam, Wai and Low, Kon Fan and Ho, Chao Yang},
booktitle = {Proceedings of the Fifteenth International Joint Conference on
Artificial Intelligence, {IJCAI-97}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {Martha E. Pollack},
pages = {745--749},
year = {1997},
note = {Information Retrieval},
url = {https://ijcai.org/proceedings/1997/108},
}
TY - CPAPER TI - Using a Bayesian Network Induction Approach for Text Categorization AU - Lam, Wai AU - Low, Kon Fan AU - Ho, Chao Yang T2 - Proceedings of the Fifteenth International Joint Conference on Artificial Intelligence, IJCAI-97 PB - International Joint Conferences on Artificial Intelligence PY - 1997 SP - 745 EP - 749 UR - https://ijcai.org/proceedings/1997/108 ER -Copied
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